ASAM OpenLABEL®

ASAM OpenLABEL defines the annotation format and labeling methods for objects and scenarios. ASAM OpenLABEL provides a guideline on how the labeling methods and definitions should be used.

From working with different customers, a significant fragmentation emerged in the way each individual organization categorizes and describes the objects populating the driving environment. Such categorizations and descriptions are the fundamental building block of any Autonomous Driving System’s (ADS) perception stack, since it is through them that an ADS comes to a basic and profound understanding of the status of around its surrounding.

The lack of a common labeling standard in the industry is the root cause of several different issues:

• Hampered Vehicle2Vehicle Interaction: The different descriptions and understandings of surroundings may cause casualties in complex situations involving two or more different ADSs
• Precluded sharing: It is a highly difficult if not impossible task to share data across organizations that adopted different labeling taxonomies and specifications
• Reduced annotation quality: Each individual labeling task requires ad-hoc training and even development of custom software functions that translate into a higher probability of errors and thus a threat to safety
• Deprecation of old labels: Long-term operation of ADS development imply changes in quantity and comprehensiveness of labels to be produced considering the evolution of the driving scenes, new sensors, and scenarios. As a consequence, a flexible descriptive language is required to absorb future extensions and modifications of labels and guarantee backward-compatibility.